Search Results for "prom-framework" - Page 7
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Showing 1413 open source projects for "prom-framework"
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CAMEL AI
Finding the Scaling Law of Agents. A multi-agent framework
...This paper explores the potential of building scalable techniques to facilitate autonomous cooperation among communicative agents and provide insight into their "cognitive" processes. To address the challenges of achieving autonomous cooperation, we propose a novel communicative agent framework named role-playing. Our approach involves using inception prompting to guide chat agents toward task completion while maintaining consistency with human intentions. We showcase how role-playing can be used to generate conversational data for studying the behaviors and capabilities of chat agents, providing a valuable resource for investigating conversational language models. -
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LLaMA-Factory
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
LLaMA-Factory is a fine-tuning and training framework for Meta's LLaMA language models. It enables researchers and developers to train and customize LLaMA models efficiently using advanced optimization techniques. -
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PentestAgent
AI agent framework for black-box security testing
PentestAgent is an open-source autonomous security testing platform designed to help organizations identify vulnerabilities and assess security posture by simulating real-world attack scenarios without manual intervention. It brings a modular and automated approach to penetration testing by orchestrating a suite of tools and scripts that can emulate common exploitation techniques, reconnaissance workflows, and post-exploitation activities across targets. Users configure rules, policies, and... -
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Agent Squad
Flexible and powerful framework for managing multiple AI agents
Agent-Squad is a flexible and powerful framework for managing multiple AI agents and handling complex conversations. It intelligently routes queries and maintains context across interactions, offering pre-built components for quick deployment and easy integration of custom agents. -
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
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PydanticAI
Agent Framework / shim to use Pydantic with LLMs
When I first found FastAPI, I got it immediately. I was excited to find something so innovative and ergonomic built on Pydantic. Virtually every Agent Framework and LLM library in Python uses Pydantic, but when we began to use LLMs in Pydantic Logfire, I couldn't find anything that gave me the same feeling. PydanticAI is a Python Agent Framework designed to make it less painful to build production-grade applications with Generative AI. Built by the team behind Pydantic (the validation layer of the OpenAI SDK, the Anthropic SDK, LangChain, LlamaIndex, AutoGPT, Transformers, CrewAI, Instructor, and many more). -
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Flet
Flet enables developers to easily build realtime web and mobile apps
...No front-end experience is required. An internal tool or a dashboard for your team, weekend project, data entry form, kiosk app or high-fidelity prototype - Flet is an ideal framework to quickly hack great-looking interactive apps to serve a group of users. No more complex architecture with JavaScript frontend, REST API backend, database, cache, etc. With Flet you just write a monolith stateful app in Python only and get a multi-user, real-time Single-Page Application (SPA). To start developing with Flet, you just need your favorite IDE or text editor. ... -
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Union Pandera
Light-weight, flexible, expressive statistical data testing library
The open-source framework for precision data testing for data scientists and ML engineers. Pandera provides a simple, flexible, and extensible data-testing framework for validating not only your data but also the functions that produce them. A simple, zero-configuration data testing framework for data scientists and ML engineers seeking correctness. Access a comprehensive suite of built-in tests, or easily create your own validation rules for your specific use cases. ... -
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RL Games
RL implementations
rl_games is a high-performance reinforcement learning framework optimized for GPU-based training, particularly in environments like robotics and continuous control tasks. It supports advanced algorithms and is built with PyTorch. -
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TrustGraph
Deploy reasoning AI agents powered by agentic graph RAG in minutes
TrustGraph is an AI-driven framework designed to assess and visualize trust relationships within networks, aiding in the analysis of trustworthiness and influence among entities. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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NErlNet
Nerlnet is a framework for research and development
NErlNet is a research-grade framework for distributed machine learning over IoT and edge devices. Built with Erlang (Cowboy HTTP), OpenNN, and Python (Flask), it enables simulation of clusters on a single machine or real deployment across heterogeneous devices. -
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GPT Academic
Research-oriented chatbot framework
GPT Academic is a research-oriented chatbot framework designed to integrate large language models (LLMs) into academic workflows. It provides tools for structured document processing, citation management, and enhanced interaction with research papers. -
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TapeAgents
A framework that facilitates all stages of LLM development
TapeAgents is a framework that facilitates all stages of the Large Language Model (LLM) agent development lifecycle, providing tools for building, testing, and deploying AI agents. -
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Backtrack Sampler
An easy-to-understand framework for LLM samplers
Backtrack Sampler is a framework designed for experimenting with custom sampling strategies for language models (LLMs), enabling the ability to rewind and revise generated tokens. It allows developers to create and test their own token generation strategies by providing a base structure for manipulating logits and probabilities, making it a flexible tool for those interested in fine-tuning the behavior of LLMs. -
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Django Ninja
Fast, Async-ready, Openapi, type hints based framework
Django Ninja is a web framework for building APIs with Django and Python 3.6+ type hints. Designed to be easy to use and intuitive. Very high performance thanks to Pydantic and async support. Type hints and automatic docs lets you focus only on business logic. Based on the open standards for APIs: OpenAPI (previously known as Swagger) and JSON Schema. Django friendly (obviously) has good integration with the Django core and ORM. -
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FinGPT
Open-Source Financial Large Language Models
FinGPT is an open-source, finance-specialized large language model framework that blends the capabilities of general LLMs with real-time financial data feeds, domain-specific knowledge bases, and task-oriented agents to support market analysis, research automation, and decision support. It extends traditional GPT-style models by connecting them to live or historical financial datasets, news APIs, and economic indicators so that outputs are grounded in relevant and recent market conditions rather than generic knowledge alone. ... -
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Edit Banana
Edit Banana: A framework for converting statistical figures
Edit Banana is an innovative web application designed to simplify image editing by merging intuitive user interfaces with powerful generative AI capabilities, enabling users to quickly enhance, manipulate, or transform photos without needing advanced design skills. It provides a smooth, browser-based experience where users can upload images, make precise edits such as background removal or inpainting, and apply stylistic transformations or corrections through AI prompts. The tool focuses on... -
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AutoAgent
AutoAgent: Fully-Automated and Zero-Code LLM Agent Framework
...The framework emphasizes self-managing workflow generation, where it can infer steps, refine them, and adapt plans even when users cannot fully specify implementation details up front. It also describes resource orchestration and iterative self-improvement behaviors, including controlled code generation for building tools and agent capabilities when needed. -
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rLLM
Democratizing Reinforcement Learning for LLMs
...The project is designed to support large-scale language models (including support for big models via integrated training backends), making it relevant for state-of-the-art research and production use. The framework includes tools for defining workflows, specifying objectives or reward functions, and managing training/policy updates across possibly distributed settings. -
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EasyR1
An Efficient, Scalable, Multi-Modality RL Training Framework
...It emphasizes memory-efficient training strategies so you can train long-context or reasoning-dense models on commodity GPUs. The framework is also organized to help you compare training strategies (e.g., pure SFT vs. preference optimization) so you can see what actually moves metrics in math, code, and multi-step reasoning. For teams exploring open reasoning models, EasyR1 provides an opinionated yet flexible path from dataset to deployable checkpoints. -
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Evals
Evals is a framework for evaluating LLMs and LLM systems
The openai/evals repository is a framework and registry for evaluating large language models and systems built with LLMs. It’s designed to let you define “evals” (evaluation tasks) in a structured way and run them against different models or agents, with the ability to score, compare, and analyze results. The framework supports templated YAML eval definitions, solver-based evaluations, custom metrics, and composition of multi-step evaluations. -
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BitNet
Inference framework for 1-bit LLMs
BitNet (bitnet.cpp) is a high-performance inference framework designed to optimize the execution of 1-bit large language models, making them more efficient for edge devices and local deployment. The framework offers significant speedups and energy reductions, achieving up to 6.17x faster performance on x86 CPUs and 70% energy savings, allowing the running of models such as the BitNet b1.58 100B with impressive efficiency. -
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django-viewflow
Reusable workflow library for Django
Viewflow is a lightweight reusable workflow library that helps to organize people collaboration business logic in Django applications. In conjunction with Django-material, they could be used as the framework to build ready-to-use business applications in minutes. Django web framework solves only technical problems related to the client-server interaction on top of the stateless HTTP protocol. Model-View-Template separation pattern helps to maintain simple CRUD-based logic. Viewflow is the library that offers an additional layer of Django web framework, allows explicitly specific people's workflow and extracts collaboration logic from Django views. ... -
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Buildbot
Python-based continuous integration testing framework
...This script can be very simple, configuring built-in components, but the full expressive power of Python is available. This allows dynamic generation of configuration, customized components, and anything else you can devise. The framework itself is implemented in Twisted Python, and compatible with all major operating systems. -
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Megatron-LM
Ongoing research training transformer models at scale
...The framework includes mixed-precision training options such as FP16, BF16, FP8, and FP4 to maximize performance and memory efficiency on modern hardware. Megatron-LM is widely used in research and industry for pretraining GPT-, BERT-, T5-, and multimodal-style models, with tooling for checkpoint conversion and interoperability with Hugging Face. -
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TradingAgents
Chinese Financial Trading Framework Based on Multi-Agent LLM
TradingAgents-CN is a Chinese-enhanced, multi-agent LLM framework aimed at building financial analysis and trading-oriented workflows, with an emphasis on collaboration between specialized agents rather than a single monolithic prompt. It organizes market-related tasks into roles and stages so different agents can contribute research, reasoning, aggregation, and decision support in a structured pipeline.
